Robert B. Gramacy
Professor of Statistics

R Packages

Local Approximate Gaussian Process Regression

laGP
is an R package providing approximate
GP regression for large computer experiments and spatial datasets.
The approximation is based on finding small local designs for prediction (independently)
at particular inputs.

Obtaining the package

Install the laGP package, from within R.R> install.packages(c("laGP"))

Optionally, install the mvtnorm, and snow packages, which are helpful for some of the comparisons in the examples and demos.R> install.packages(c("mvtnorm", "snow"))

Load the library as you would for any R library.R> library(laGP)

Documentation

The laGPtutorial is
implemented as a package vignette, authored in Sweave.
The pdf can be obtained from within R with the following code.R> vignette("laGP")

To obtain the source code contained in the vignette, use the Stangle command.R> v R> Stangle(paste(v$Dir, "/doc/", v$File, sep=""))

The code from Section 4 of the vignette, on Calibration, is available as a standalone demo.R> demo("calib", package="laGP")

See the package documentation.
A pdf
version of the reference manual, or help pages, as also available.
The help pages can be accessed from within R.
Try starting with:R> help(package=laGP)R> ?laGP # follow the examples R> ?aGP # follow the examples - this is the main workhorse